Untitled

Pain > (Vicarious & Cognitive)

Pain > VC :: load dataset

mount_dir = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel';
con_list = dir(fullfile(mount_dir, '*/con_0009.nii'));
spm('Defaults','fMRI') 
con_fldr = {con_list.folder}; fname = {con_list.name};
con_files = strcat(con_fldr,'/', fname)';
con_data_obj = fmri_data(con_files);
Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii
sampleto = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0009.nii'
loading mask. mapping volumes. 
checking that dimensions and voxel sizes of volumes are the same. 
Pre-allocating data array. Needed: 25558272 bytes
Loading image number:    64
Elapsed time is 132.792357 seconds.
Image names entered, but fullpath attribute is empty. Getting path info.
Number of unique values in dataset: 6191567  Bit rate: 22.56 bits
contrast_name = {'cue_P', 'cue_V', 'cue_C', 'cue_G',...
    'cueXcue_P', 'cueXcue_V', 'cueXcue_C', 'cueXcue_G',...
    'stim_P', 'stim_V', 'stim_C', 'stim_G',...
    'stimXcue_P', 'stimXcue_V', 'stimXcue_C', 'stimXcue_G',...
    'motor', ...
    'simple_cue_P', 'simple_cue_V', 'simple_cue_C',...
    'simple_cueXcue_P', 'simple_cueXcue_V', 'simple_cueXcue_C', ...
    'simple_stim_P', 'simple_stim_V', 'simple_stim_C',...
    'simple_stimXcue_P', 'simple_stimXcue_V', 'simple_stimXcue_C'};

Pain > VC :: check data coverage

m = mean(con_data_obj);
m.dat = sum(~isnan(con_data_obj.dat) & con_data_obj.dat ~= 0, 2);
orthviews(m, 'trans') % display
SPM12: spm_check_registration (v7759)              01:32:34 - 26/05/2022
========================================================================
Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1
Grouping contiguous voxels:   1 regions
ans = 1×1 cell array
    {1×1 region}

Pain > VC :: Plot diagnostics, before l2norm

drawnow; snapnow

[wh_outlier_uncorr, wh_outlier_corr] = plot(con_data_obj)

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 5 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 18.75% Expected 3.20 outside 95% ellipsoid, found 5 Potential outliers based on mahalanobis distance: Bonferroni corrected: 3 images Cases 24 33 35 Uncorrected: 5 images Cases 2 24 33 34 35 Retained 7 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 45.31% Expected 3.20 outside 95% ellipsoid, found 4 Potential outliers based on mahalanobis distance: Bonferroni corrected: 0 images Cases Uncorrected: 4 images Cases 17 20 33 60 Mahalanobis (cov and corr, q<0.05 corrected): 3 images Outlier_count Percentage _____________ __________ global_mean 1 1.5625 global_mean_to_variance 0 0 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 3 4.6875 mahal_cov_uncor 5 7.8125 mahal_cov_corrected 3 4.6875 mahal_corr_uncor 4 6.25 mahal_corr_corrected 0 0 Overall_uncorrected 8 12.5 Overall_corrected 4 6.25

SPM12: spm_check_registration (v7759) 01:33:10 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

wh_outlier_uncorr = 64×1 logical array

wh_outlier_corr = 64×1 logical array

Pain > VC :: run robfit

set(gcf,'Visible','on')
figure ('Visible', 'on');
drawnow, snapnow;

Pain > VC :: remove outliers based on plot

con = con_data_obj;
disp(strcat("current length is ", num2str(size(con_data_obj.dat,2))))
current length is 64
%for s = 1:length(wh_outlier_corr)
    %disp(strcat("-------subject", num2str(s), "------"))
con.dat = con_data_obj.dat(:,~wh_outlier_corr);
con.image_names = con_data_obj.image_names(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×60 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [60×12 char]
              fullpath: [64×109 char]
           files_exist: [64×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0009.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.fullpath = con_data_obj.fullpath(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×60 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [60×12 char]
              fullpath: [60×109 char]
           files_exist: [64×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0009.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.files_exist = con_data_obj.files_exist(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×60 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [60×12 char]
              fullpath: [60×109 char]
           files_exist: [60×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0009.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
%end
disp(strcat("after removing ", num2str(sum(wh_outlier_corr)), " participants, size is now ",num2str(size(con.dat,2))))
after removing 4 participants, size is now 60

Pain > VC :: plot diagnostics, after l2norm

imgs2 = con.rescale('l2norm_images');

Pain > VC :: ttest

t = ttest(imgs2);

One-sample t-test Calculating t-statistics and p-values

orthviews(t)

SPM12: spm_check_registration (v7759) 01:33:15 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

fdr_t = threshold(t, .05, 'fdr');

Image 1 FDR q < 0.050 threshold is 0.029630 Image 1 32 contig. clusters, sizes 1 to 58721 Positive effect: 28826 voxels, min p-value: 0.00000000 Negative effect: 30338 voxels, min p-value: 0.00000000

orthviews(fdr_t)

SPM12: spm_check_registration (v7759) 01:33:17 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×32 struct}

drawnow, snapnow;

create_figure('montage'); axis off

montage(fdr_t)

Setting up fmridisplay objects

sagittal montage: 1390 voxels displayed, 57774 not displayed on these slices

sagittal montage: 1292 voxels displayed, 57872 not displayed on these slices

sagittal montage: 1293 voxels displayed, 57871 not displayed on these slices

axial montage: 10730 voxels displayed, 48434 not displayed on these slices

axial montage: 11645 voxels displayed, 47519 not displayed on these slices

ans =

fmridisplay with properties: overlay: '/Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img' SPACE: [1×1 struct] activation_maps: {[1×1 struct]} montage: {[1×1 struct] [1×1 struct] [1×1 struct] [1×1 struct] [1×1 struct]} surface: {} orthviews: {} history: {} history_descrip: [] additional_info: ''

drawnow, snapnow;

Vicarious > (Pain & Cognitive)

clear all

Vicarious > PC :: load dataset

mount_dir = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel';
con_list = dir(fullfile(mount_dir, '*/con_0010.nii'));
spm('Defaults','fMRI') 
con_fldr = {con_list.folder}; fname = {con_list.name};
con_files = strcat(con_fldr,'/', fname)';
con_data_obj = fmri_data(con_files);
Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii
Direct calls to spm_defauts are deprecated.
Please use spm('Defaults',modality) or spm_get_defaults instead.
sampleto = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0010.nii'
loading mask. mapping volumes. 
checking that dimensions and voxel sizes of volumes are the same. 
Pre-allocating data array. Needed: 25558272 bytes
Loading image number:    64
Elapsed time is 124.339117 seconds.
Image names entered, but fullpath attribute is empty. Getting path info.
Number of unique values in dataset: 6187555  Bit rate: 22.56 bits
contrast_name = {'cue_P', 'cue_V', 'cue_C', 'cue_G',...
    'cueXcue_P', 'cueXcue_V', 'cueXcue_C', 'cueXcue_G',...
    'stim_P', 'stim_V', 'stim_C', 'stim_G',...
    'stimXcue_P', 'stimXcue_V', 'stimXcue_C', 'stimXcue_G',...
    'motor', ...
    'simple_cue_P', 'simple_cue_V', 'simple_cue_C',...
    'simple_cueXcue_P', 'simple_cueXcue_V', 'simple_cueXcue_C', ...
    'simple_stim_P', 'simple_stim_V', 'simple_stim_C',...
    'simple_stimXcue_P', 'simple_stimXcue_V', 'simple_stimXcue_C'};

Vicarious > PC :: check data coverage

m = mean(con_data_obj);

m.dat = sum(~isnan(con_data_obj.dat) & con_data_obj.dat ~= 0, 2);

orthviews(m, 'trans') % display

SPM12: spm_check_registration (v7759) 01:35:52 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

ans = 1×1 cell array

{1×1 region}

Vicarious > PC :: Plot diagnostics, before l2norm

drawnow; snapnow

[wh_outlier_uncorr, wh_outlier_corr] = plot(con_data_obj)

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 5 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 20.31% Expected 3.20 outside 95% ellipsoid, found 6 Potential outliers based on mahalanobis distance: Bonferroni corrected: 5 images Cases 2 24 33 35 38 Uncorrected: 6 images Cases 2 24 33 35 38 43 Retained 10 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 45.31% Expected 3.20 outside 95% ellipsoid, found 2 Potential outliers based on mahalanobis distance: Bonferroni corrected: 1 images Cases 11 Uncorrected: 2 images Cases 11 62 Mahalanobis (cov and corr, q<0.05 corrected): 6 images Outlier_count Percentage _____________ __________ global_mean 2 3.125 global_mean_to_variance 0 0 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 1 1.5625 mahal_cov_uncor 6 9.375 mahal_cov_corrected 5 7.8125 mahal_corr_uncor 2 3.125 mahal_corr_corrected 1 1.5625 Overall_uncorrected 8 12.5 Overall_corrected 6 9.375

SPM12: spm_check_registration (v7759) 01:36:34 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

wh_outlier_uncorr = 64×1 logical array

wh_outlier_corr = 64×1 logical array

Vicarious > PC :: run robfit

set(gcf,'Visible','on')
figure ('Visible', 'on');
drawnow, snapnow;

Vicarious > PC :: remove outliers based on plot

con = con_data_obj;
disp(strcat("current length is ", num2str(size(con_data_obj.dat,2))))
current length is 64
%for s = 1:length(wh_outlier_corr)
  %  disp(strcat("-------subject", num2str(s), "------"))
con.dat = con_data_obj.dat(:,~wh_outlier_corr);
con.image_names = con_data_obj.image_names(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×58 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [58×12 char]
              fullpath: [64×109 char]
           files_exist: [64×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0010.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.fullpath = con_data_obj.fullpath(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×58 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [58×12 char]
              fullpath: [58×109 char]
           files_exist: [64×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0010.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.files_exist = con_data_obj.files_exist(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×58 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [58×12 char]
              fullpath: [58×109 char]
           files_exist: [58×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0010.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
%end
disp(strcat("after removing ", num2str(sum(wh_outlier_corr)), " participants, size is now ",num2str(size(con.dat,2))))
after removing 6 participants, size is now 58

Vicarious > PC :: plot diagnostics, after l2norm

imgs2 = con.rescale('l2norm_images');

Vicarious > PC :: ttest

t = ttest(imgs2);

One-sample t-test Calculating t-statistics and p-values

orthviews(t)

SPM12: spm_check_registration (v7759) 01:36:40 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

fdr_t = threshold(t, .05, 'fdr');

Image 1 FDR q < 0.050 threshold is 0.031548 Image 1 17 contig. clusters, sizes 1 to 62394 Positive effect: 27674 voxels, min p-value: 0.00000000 Negative effect: 35332 voxels, min p-value: 0.00000000

orthviews(fdr_t)

SPM12: spm_check_registration (v7759) 01:36:41 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×17 struct}

drawnow, snapnow;

create_figure('montage'); axis off

montage(fdr_t)

Setting up fmridisplay objects

sagittal montage: 1568 voxels displayed, 61438 not displayed on these slices

sagittal montage: 1631 voxels displayed, 61375 not displayed on these slices

sagittal montage: 1629 voxels displayed, 61377 not displayed on these slices

axial montage: 11574 voxels displayed, 51432 not displayed on these slices

axial montage: 12560 voxels displayed, 50446 not displayed on these slices

ans =

drawnow, snapnow;

Cognitive > (Pain & Vicarious)

Cognitive > PV :: load dataset

mount_dir = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel';
con_list = dir(fullfile(mount_dir, '*/con_0010.nii'));
spm('Defaults','fMRI') 
con_fldr = {con_list.folder}; fname = {con_list.name};
con_files = strcat(con_fldr,'/', fname)';
con_data_obj = fmri_data(con_files);
Using default mask: /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/brainmask_canlab.nii
sampleto = '/Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0010.nii'
loading mask. mapping volumes. 
checking that dimensions and voxel sizes of volumes are the same. 
Pre-allocating data array. Needed: 25558272 bytes
Loading image number:    64
Elapsed time is 139.883295 seconds.
Image names entered, but fullpath attribute is empty. Getting path info.
Number of unique values in dataset: 6187555  Bit rate: 22.56 bits
contrast_name = {'cue_P', 'cue_V', 'cue_C', 'cue_G',...
    'cueXcue_P', 'cueXcue_V', 'cueXcue_C', 'cueXcue_G',...
    'stim_P', 'stim_V', 'stim_C', 'stim_G',...
    'stimXcue_P', 'stimXcue_V', 'stimXcue_C', 'stimXcue_G',...
    'motor', ...
    'simple_cue_P', 'simple_cue_V', 'simple_cue_C',...
    'simple_cueXcue_P', 'simple_cueXcue_V', 'simple_cueXcue_C', ...
    'simple_stim_P', 'simple_stim_V', 'simple_stim_C',...
    'simple_stimXcue_P', 'simple_stimXcue_V', 'simple_stimXcue_C'};

Cognitive > PV :: check data coverage

m = mean(con_data_obj);

m.dat = sum(~isnan(con_data_obj.dat) & con_data_obj.dat ~= 0, 2);

orthviews(m, 'trans') % display

SPM12: spm_check_registration (v7759) 01:39:37 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

ans = 1×1 cell array

{1×1 region}

Cognitive > PV :: Plot diagnostics, before l2norm

drawnow; snapnow

[wh_outlier_uncorr, wh_outlier_corr] = plot(con_data_obj)

______________________________________________________________ Outlier analysis ______________________________________________________________ global mean | global mean to var | spatial MAD | Missing values | 0 images Retained 5 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 20.31% Expected 3.20 outside 95% ellipsoid, found 6 Potential outliers based on mahalanobis distance: Bonferroni corrected: 5 images Cases 2 24 33 35 38 Uncorrected: 6 images Cases 2 24 33 35 38 43 Retained 10 components for mahalanobis distance Expected 50% of points within 50% normal ellipsoid, found 45.31% Expected 3.20 outside 95% ellipsoid, found 2 Potential outliers based on mahalanobis distance: Bonferroni corrected: 1 images Cases 11 Uncorrected: 2 images Cases 11 62 Mahalanobis (cov and corr, q<0.05 corrected): 6 images Outlier_count Percentage _____________ __________ global_mean 2 3.125 global_mean_to_variance 0 0 missing_values 0 0 rmssd_dvars 0 0 spatial_variability 1 1.5625 mahal_cov_uncor 6 9.375 mahal_cov_corrected 5 7.8125 mahal_corr_uncor 2 3.125 mahal_corr_corrected 1 1.5625 Overall_uncorrected 8 12.5 Overall_corrected 6 9.375

SPM12: spm_check_registration (v7759) 01:40:09 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 (all) /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1 /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

Grouping contiguous voxels: 1 regions

wh_outlier_uncorr = 64×1 logical array

wh_outlier_corr = 64×1 logical array

Cognitive > PV :: run robfit

set(gcf,'Visible','on')
figure ('Visible', 'on');
drawnow, snapnow;

Cognitive > PV :: remove outliers based on plot

con = con_data_obj;
disp(strcat("current length is ", num2str(size(con_data_obj.dat,2))))
current length is 64
%for s = 1:length(wh_outlier_corr)
   % disp(strcat("-------subject", num2str(s), "------"))
con.dat = con_data_obj.dat(:,~wh_outlier_corr);
con.image_names = con_data_obj.image_names(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×58 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [58×12 char]
              fullpath: [64×109 char]
           files_exist: [64×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0010.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.fullpath = con_data_obj.fullpath(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×58 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [58×12 char]
              fullpath: [58×109 char]
           files_exist: [64×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0010.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
con.files_exist = con_data_obj.files_exist(~wh_outlier_corr,:)
con = 
  fmri_data with properties:

          source_notes: 'Info about image source here'
                     X: []
                  mask: [1×1 fmri_mask_image]
          mask_descrip: 'REMOVED: CHANGED SPACE'
    images_per_session: []
                     Y: []
               Y_names: []
             Y_descrip: 'Behavioral or outcome data matrix.'
            covariates: []
       covariate_names: {''}
    covariates_descrip: 'Nuisance covariates associated with data'
       history_descrip: 'Cell array of names of methods applied to this data, in order'
       additional_info: [0×0 struct]
        metadata_table: [0×0 table]
                   dat: [99837×58 single]
           dat_descrip: []
               volInfo: [1×1 struct]
        removed_voxels: 0
        removed_images: 0
           image_names: [58×12 char]
              fullpath: [58×109 char]
           files_exist: [58×1 logical]
               history: {''  'Sampled to space of /Volumes/spacetop_projects_social/analysis/fmri/spm/univariate/model-02_CcEScA/1stLevel/sub-0003/con_0010.nii'  'Masked with REMOVED: CHANGED SPACE'  'Checked image files exist. All exist =   1'}
%end
disp(strcat("after removing ", num2str(sum(wh_outlier_corr)), " participants, size is now ",num2str(size(con.dat,2))))
after removing 6 participants, size is now 58

Cognitive > PV:: plot diagnostics, after l2norm

imgs2 = con.rescale('l2norm_images');

Cognitive > PV :: ttest

t = ttest(imgs2);

One-sample t-test Calculating t-statistics and p-values

orthviews(t)

SPM12: spm_check_registration (v7759) 01:40:15 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×1 struct}

drawnow, snapnow;

fdr_t = threshold(t, .05, 'fdr');

Image 1 FDR q < 0.050 threshold is 0.031548 Image 1 17 contig. clusters, sizes 1 to 62394 Positive effect: 27674 voxels, min p-value: 0.00000000 Negative effect: 35332 voxels, min p-value: 0.00000000

orthviews(fdr_t)

SPM12: spm_check_registration (v7759) 01:40:16 - 26/05/2022 ======================================================================== Display /Users/h/Documents/MATLAB/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/keuken_2014_enhanced_for_underlay.img,1

ans = 1×1 cell array

{1×17 struct}

drawnow, snapnow;

create_figure('montage'); axis off

montage(fdr_t)

Setting up fmridisplay objects

sagittal montage: 1568 voxels displayed, 61438 not displayed on these slices

sagittal montage: 1631 voxels displayed, 61375 not displayed on these slices

sagittal montage: 1629 voxels displayed, 61377 not displayed on these slices

axial montage: 11574 voxels displayed, 51432 not displayed on these slices

axial montage: 12560 voxels displayed, 50446 not displayed on these slices

ans =

drawnow, snapnow;